Genome-wide multi-trait analysis on cardioembolic stroke identifies 47 novel loci

Author:

Meseguer Monfort L1,Ahlberg G1,Andreasen L1,Ghouse J1,Haunso S1,Bundgaard H1,Svendsen J H1,Olesen M S1

Affiliation:

1. Rigshospitalet - Copenhagen University Hospital , Copenhagen , Denmark

Abstract

Abstract Background Ischemic stroke is one of the leading causes of death and disability-adjusted life-years worldwide. It has several subtypes and cardioembolic stroke (CES) accounts for 15–30% of ischemic strokes. Atrial fibrillation (AF) is the most important risk factor for CES. AF increases the risk of stroke up to 5-fold and there is a substantial overlap in the aetiology of AF and CES. Large genome-wide association studies (GWAS) on AF have identified more than 150 common and rare genetic variants. However, the difficulty in acquiring large sample sizes of CES cohorts has hindered the genetic description of the disease. Purpose In this study, we mapped the genetics of CES to increase our understanding of the molecular biology driving the disease. By leveraging the large genetic cohorts of AF through a multi-trait analysis of AF and CES, we aimed to bypass the lack of statistical power for studying the genetics of CES. Methods First, we obtained the largest possible sample size of AF GWAS by conducting a meta-analysis on publicly available summary statistics from the FinnGen study (v5) and the largest multi-ethnic meta-analysis on AF to date. Summary statistics for stroke were obtained from the largest multi-ancestry GWAS on stroke to date, MEGASTROKE, which examined different ancestries and stroke subtypes. Multi-trait analysis requires a high genetic correlation. Genetic correlations between the different stroke summary statistics and the AF meta-analysis were assessed with LD Score Regression. Second, we performed a joint meta-analysis of CES with MTAG using the CES summary statistics from MEGASTROKE and the AF GWAS meta-analysis. MTAG recalculates p-values and effect sizes for each trait separately by leveraging the covariation for correlated traits. The MTAG-computed summary statistics for CES and AF were subjected to genomic loci characterisation, with functional and annotation analysis carried out by FUMA. Results We show a high genetic correlation between CES and AF (rg = 0.88). Using MTAG, the GWAS meta-analysis of CES increased the effective sample size by almost 3 folds (n=24,639, Table 1). We discovered 50 CES loci whereof 47 are novel (Fig. 1). We mapped 101 genes to CES MTAG computed summary statistics, obtaining enrichment in gene sets involved in cardiac conduction and contraction, cardiac tissue development and cranial skeleton morphogenesis. Conclusion In conclusion, we identified 47 novel CES loci and demonstrated a substantial shared genetic variation with AF. We furthermore mapped 98 genes not previously linked to CES by AF. These results represent findings that potentially could be used for antithrombotic drug discovery and are a major advance in our understanding of the genetic underpinnings of CES Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): John and Birthe Meyer Foundation, the Research Foundation of the Heart Centre, Rigshospitalet, the Research Council at Rigshospitalet.The Hallas-Møller Emerging Investigator Novo Nordisk (NNF17OC0031204), Arvid Nilsson Foundation

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine

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